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CASPredict: a web service for identifying Cas proteins

Clustered regularly interspaced short palindromic repeats (CRISPR) and their associated (Cas) proteins constitute the CRISPR-Cas systems, which play a key role in prokaryote adaptive immune system against invasive foreign elements. In recent years, the CRISPR-Cas systems have also been designed to f...

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Detalles Bibliográficos
Autores principales: Yang, Shanshan, Huang, Jian, He, Bifang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8327967/
https://www.ncbi.nlm.nih.gov/pubmed/34395100
http://dx.doi.org/10.7717/peerj.11887
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author Yang, Shanshan
Huang, Jian
He, Bifang
author_facet Yang, Shanshan
Huang, Jian
He, Bifang
author_sort Yang, Shanshan
collection PubMed
description Clustered regularly interspaced short palindromic repeats (CRISPR) and their associated (Cas) proteins constitute the CRISPR-Cas systems, which play a key role in prokaryote adaptive immune system against invasive foreign elements. In recent years, the CRISPR-Cas systems have also been designed to facilitate target gene editing in eukaryotic genomes. As one of the important components of the CRISPR-Cas system, Cas protein plays an irreplaceable role. The effector module composed of Cas proteins is used to distinguish the type of CRISPR-Cas systems. Effective prediction and identification of Cas proteins can help biologists further infer the type of CRISPR-Cas systems. Moreover, the class 2 CRISPR-Cas systems are gradually applied in the field of genome editing. The discovery of Cas protein will help provide more candidates for genome editing. In this paper, we described a web service named CASPredict (http://i.uestc.edu.cn/caspredict/cgi-bin/CASPredict.pl) for identifying Cas proteins. CASPredict first predicts Cas proteins based on support vector machine (SVM) by using the optimal dipeptide composition and then annotates the function of Cas proteins based on the hmmscan search algorithm. The ten-fold cross-validation results showed that the 84.84% of Cas proteins were correctly classified. CASPredict will be a useful tool for the identification of Cas proteins, or at least can play a complementary role to the existing methods in this area.
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spelling pubmed-83279672021-08-13 CASPredict: a web service for identifying Cas proteins Yang, Shanshan Huang, Jian He, Bifang PeerJ Bioinformatics Clustered regularly interspaced short palindromic repeats (CRISPR) and their associated (Cas) proteins constitute the CRISPR-Cas systems, which play a key role in prokaryote adaptive immune system against invasive foreign elements. In recent years, the CRISPR-Cas systems have also been designed to facilitate target gene editing in eukaryotic genomes. As one of the important components of the CRISPR-Cas system, Cas protein plays an irreplaceable role. The effector module composed of Cas proteins is used to distinguish the type of CRISPR-Cas systems. Effective prediction and identification of Cas proteins can help biologists further infer the type of CRISPR-Cas systems. Moreover, the class 2 CRISPR-Cas systems are gradually applied in the field of genome editing. The discovery of Cas protein will help provide more candidates for genome editing. In this paper, we described a web service named CASPredict (http://i.uestc.edu.cn/caspredict/cgi-bin/CASPredict.pl) for identifying Cas proteins. CASPredict first predicts Cas proteins based on support vector machine (SVM) by using the optimal dipeptide composition and then annotates the function of Cas proteins based on the hmmscan search algorithm. The ten-fold cross-validation results showed that the 84.84% of Cas proteins were correctly classified. CASPredict will be a useful tool for the identification of Cas proteins, or at least can play a complementary role to the existing methods in this area. PeerJ Inc. 2021-07-30 /pmc/articles/PMC8327967/ /pubmed/34395100 http://dx.doi.org/10.7717/peerj.11887 Text en © 2021 Yang et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Yang, Shanshan
Huang, Jian
He, Bifang
CASPredict: a web service for identifying Cas proteins
title CASPredict: a web service for identifying Cas proteins
title_full CASPredict: a web service for identifying Cas proteins
title_fullStr CASPredict: a web service for identifying Cas proteins
title_full_unstemmed CASPredict: a web service for identifying Cas proteins
title_short CASPredict: a web service for identifying Cas proteins
title_sort caspredict: a web service for identifying cas proteins
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8327967/
https://www.ncbi.nlm.nih.gov/pubmed/34395100
http://dx.doi.org/10.7717/peerj.11887
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